An evolutionary approach to designing complex spreading codes for DS-CDMA

This paper proposes a novel evolutionary approach to spreading code design in direct sequence code division multiple access (DS-CDMA). Specifically, a multiobjective evolutionary algorithm (EA) is used to generate complex spreading sequences that are optimized with respect to the average mean-square cross- and/or autocorrelation (CC and/or AC) properties. A theoretical model is developed in order to demonstrate the optimality of the generated codes. The proposed algorithm enables spreading code design with no constraints on the code length. Furthermore, it is possible to generate K/spl ges/N codes of length N with very little cost in correlation properties. This results in significant capacity enhancement in DS-CDMA systems.     

An evolutionary approach for gene expression patterns

This study presents an evolutionary algorithm, called a heterogeneous selection genetic algorithm (HeSGA), for analyzing the patterns of gene expression on microarray data. Microarray technologies have provided the means to monitor the expression levels of a large number of genes simultaneously. Gene clustering and gene ordering are important in analyzing a large body of microarray expression data. The proposed method simultaneously solves gene clustering and gene-ordering problems by integrating global and local search mechanisms. Clustering and ordering information is used to identify functionally related genes and to infer genetic networks from immense microarray expression data. HeSGA was tested on eight test microarray datasets, ranging in size from 147 to 6221 genes. The experimental clustering and visual results indicate that HeSGA not only ordered genes smoothly but also grouped genes with similar gene expressions. Visualized results and a new scoring function that references predefined functional categories were employed to confirm the biological interpretations of results yielded using HeSGA and other methods. These results indicate that HeSGA has potential in analyzing gene expression patterns.     

An evolutionary approach to materialized views selection in a datawarehouse environment

A data warehouse (DW) contains multiple views accessed by queries. One of the most important decisions in designing a DW is selecting views to materialize for the purpose of efficiently supporting decision making. The search space for possible materialized views is exponentially large. Therefore heuristics have been used to search for a near optimal solution. In this paper, we explore the use of an evolutionary algorithm for materialized view selection based on multiple global processing plans for queries. We apply a hybrid evolutionary algorithm to solve three related problems. The first is to optimize queries. The second is to choose the best global processing plan from multiple global processing plans. The third is to select materialized views from a given global processing plan. Our experiment shows that the hybrid evolutionary algorithm delivers better performance than either the evolutionary algorithm or heuristics used alone in terms of the minimal query and maintenance cost and the evaluation cost to obtain the minimal cost     

一种电动汽车用GPS导航系统的设计

近年限于环境和能源的压力,电动汽车及相关产业受到国内外广泛关注.电动汽车正常工作的前提是需要充足的电能,以至于及时为车载动力电池补充电能成为关键.该文分别从硬件和软件两方面介绍了一种基于ARM+Windows CE 6.0平台的车载导航系统.该系统采用GPS和GPRS相结合的技术,实现了在电动汽车电池电量低的情况下,通...     

Depolarizing trihedral corner reflectors for radar navigation andremote sensing

A conventional trihedral corner reflector can be modified to present either a twist-polarizing or a circularly polarizing response by adding conducting fins of rectangular corrugations of prescribed dimensions and orientation to one of its interior surfaces. Since the modified reflector retains most of the mechanical ruggedness and ease of manufacture of the original, it is suitable for deployment in the field for extended periods as required in radar navigation and remote sensing applications. For most directions of incidence the response of the reflector is dominated by triple-bounce reflections from the interior and is a function of the size and shape of the reflecting panels, the dimensions of the corrugations, and the orientation of the reflector with respect to the radar. Experimental results show that prototype twist-polarizing and circularly polarizing reflectors respond as predicted     

An output-feedback fuzzy approach to guaranteed cost control of vehicle lateral motion

This paper introduces a fuzzy guaranteed cost control approach for automated steering of a highway vehicle. The Takagi–Sugeno (T–S) fuzzy model is utilized to depict the dynamics of nonlinear time-varying lateral system. Based on the fuzzy model, an observer-based fuzzy controller is developed so that without knowing road’s curvature the vehicle can track center of the present lane on a curved highway section. Integrating H_∞ control and optimal control strategies, the fuzzy controller and observer are formulated by solving a minimization problem, which is to minimize a given quadratic performance function. Sufficient conditions to ensure minimum upper bound of the performance function are derived in terms of linear matrix inequalities (LMIs). Therefore, the designing work can be efficiently completed by applying the convex optimization techniques. Verified by computer simulation, the proposed method can perform well in driving safety and ride comfort.     

An adaptive approach to spectral analysis of pattern-reversal visual evoked potentials

A method for spectral analysis of pattern-reversal visual evoked potentials (PRVEP's) is presented that results in spectral peaks of uniform width in the frequency domain for signals with a wide range of time-domain duration. Uniformity of spectral peak width is necessary for accurate comparison of spectra. The desired frequency domain characteristics can be achieved through the application of "tunable" data windows prior to transformation. The Io-sinh (Kaiser), Gaussian, and cosine-taper (Tukey) windows were evaluated as to their ability to produce power spectra with uniform spectral peak width. Objective comparison of power spectra is based on the "spectral parameter," which is a numerical index of power distribution. Application of the method to PRVEP waveforms of normal subjects (N = 20) and to a population of Alzheimer's Disease patients (N = 15) showed the Io-sinh window to be the most effective method, yielding correct classification of all normal and abnormal subjects. The Gaussian window also performed well, with only two misclassifications. Use of the rectangular window resulted in seven misclassifications. The tapered-cosine window was very limited in its applicability, and was about equal in performance to the rectangular window.     

陆用车载组合导航系统里程仪快速标定

为减小里程仪刻度因子误差对组合导航精度的影响,分析了安装误差以及轮胎内外温度与里程仪刻度因子的关系,提出组合导航系统中里程仪快速标定法,推导出组合导航系统卡尔曼滤波方程,进行系统仿真。结果表明,将里程仪刻度系数进行标定后,里程仪刻度系数误差明显提高两个量级,里程仪测量输出数据的准确度也明显提高,同时组合导航的定位精度也得到了提高。     

A mechatronic sensing system for vehicle guidance and control

Magnetic sensing is used for control and guidance in intelligent transportation systems (ITS). This includes vehicle applications such as lane-keeping in intelligent cruise control as well as driver assistance in highway maintenance functions such as snow removal. This paper presents a new mechatronic magnetic sensing system for ITS. The new system has several advantages both in terms of its hardware design and its underlying reference detection algorithms, providing a significant improvement in performance, maintainability, and upgradability over existing systems. It is a mechatronic system in that it combines mechanical position sensing with electronics implementation of the hardware and the underlying algorithms.     

A lateral position sensing system for automated vehicle following

This paper investigates the use of photoresistive light sensor arrays as a possible lateral position sensing system for a vehicle, or several vehicles, following a lead vehicle under separate control. A brief motivation for the use of such a sensing array is followed by a derivation of an appropriate sensor layout. It is shown that the sensing array has several benefits, including cost, simplicity, redundancy, and near linearity. Experimental results are given for a scaled vehicle following manoeuvre using a simple lateral control strategy. The results show that the sensor array may be attractive for lateral alignment in vehicle-following manoeuvres     

An optimization based approach to enhance the throughput and energy efficiency for cognitive unmanned aerial vehicle networks

Wireless Networks - Unmanned aerial vehicle (UAV) is a promising technology to serve as a mission-critical communication, where human operation or intervention is risky, dangerous, impossible or...     

基于期望最大化算法的车载导航定位

随着GPS车载导航系统的普及,围绕车载导航系统性能的研究主要集中在了如何提高导航精度的问题上.然而,车载导航应用的特殊环境决定了传统的精度提高方法的局限性.文中首先简述了车载导航的特殊环境,然后在此基础上提出了利用EM(Expectation Maximization,期望最大化)算法提高导航状态解算精度的构想.通过使用平淡卡尔曼滤波,解决了期望最大化两步算法中的第一步即状态估计问题.基于实测数据的仿真结果证明,该方法能够有效地提高车载环境下接收机的定位精度和稳定性,进而提高车载导航的服务质量.     

基于MEMS技术的微型组合导航传感系统研究

大型无人机的航姿系统、大气数据系统及惯性导航系统等导航设备因结构复杂、体积、重量大及价格昂贵等因素,无法在微型无人机(MAV)上使用.本文采用PC104嵌入式微机、MEMS集成技术、数据融合技术及GALILEO技术,实现了一种用于微型无人机的微型组合导航传感系统.以C语言及汇编语言作为系统软件的开发平台,增强了系统软件的可维护性及可扩展性.该系统集飞机航姿系统、大气数据系统、惯性导航传感器等功能于一身.实验室和现场的测试结果表明,该传感系统提高了导航精度,简化了结构,缩小了体积,减轻了重量.该系统拟用于微型无人机.     

一种改进的地图匹配技术在车载导航系统中的应用

本文在研究地图匹配算法的基础之上,提出了一种改进的地图匹配算法,利用该算法绝大多数(>96%)定位数据都能相对准确地匹配到道路上,匹配后的定位精度得到提高;匹配算法实现了实时,能够满足实际需要(1次/s);在GPS受到一定程度的遮挡时系统能够正常识别并且匹配.     

Image representation by compressive sensing for visual sensor networks

This paper addresses the image representation problem in visual sensor networks. We propose a new image representation method for visual sensor networks based on compressive sensing (CS). CS is a new sampling method for sparse signals, which is able to compress the input data in the sampling process. Combining both signal sampling and data compression, CS is more capable of image representation for reducing the computation complexity in image/video encoder in visual sensor networks where computation resource is extremely limited. Since CS is more efficient for sparse signals, in our scheme, the input image is firstly decomposed into two components, i.e., dense and sparse components; then the dense component is encoded by the traditional approach (JPEG or JPEG 2000) while the sparse component is encoded by a CS technique. In order to improve the rate distortion performance, we leverage the strong correlation between dense and sparse components by using a piecewise autoregressive model to construct a prediction of the sparse component from the corresponding dense component. Given the measurements and the prediction of the sparse component as initial guess, we use projection onto convex set (POCS) to reconstruct the sparse component. Our method considerably reduces the number of random measurements needed for CS reconstruction and the decoding computational complexity, compared to the existing CS methods. In addition, our experimental results show that our method may achieves up to 2 dB gain in PSNR over the existing CS based schemes, for the same number of measurements.     

无人机卫星导航的接收定位故障实验

向飞行提供精确的方向和位置坐标,并且根据姿态信息对飞机飞行的状态进行预测,这些就是组合定位定向导航系统需要完成的任务。结合了相关竞争能定位软件的应用,在最大程度上保证了无人飞机的自主飞行。但是在精确定位中,总会有故障发生,这就需要将故障资源合理分析,并针对相关分析结果,优化无人机卫星导航定位技术。     

A neural-network approach to radiometric sensing of land-surfaceparameters

A biophysically-based land-surface process/radiobrightness (LSP/R) model is integrated with a dynamic learning neural network (DLNN) to retrieve the land-surface parameters from its radiometric signatures. Predictions from the LSP/R model are used to train the DLNN and serve as the reference for evaluation of the DLNN retrievals. Both horizontally polarized and vertically polarized brightnesses at 1.4 GHz, 19 GHz, and 37 GHz for an incidence angle of 53° make up the input nodes of the DLNN. The corresponding output nodes are composed of land-surface parameters, canopy temperature and water content, and soil temperature and moisture (uppermost 5 mm). Under no-noise conditions, the maximum of the root mean-square (RMS) errors between the retrieved parameters of interest and their corresponding reference from the LSP/R model is smaller than 28 for a four-channel case with 19 GHz and 37 GHz brightnesses as the inputs of the DLNN. The maximum RMS error is reduced to within 0.5% if additional 1.4 GHz brightnesses are used (a six-channel case). This indicates that the DLNN produces negligible errors onto its retrievals. For the realization of the problem, two different levels of noises are added to the input nodes. The noises are assumed to be Gaussian distributed with standard deviations of 1 K and 2 K. The maximum RMS errors are increased to 9.3% and 10.3% for the 1 K-noise and 2 K-noise cases, respectively, for the four-channel ease. They are reduced to 6.0% and 9.1% for the 1 K-noise and 2 K-noise cases, respectively, for the six-channel case. This is an implication that 1.4 GHz is a better frequency in probing soil parameters than 19 GHz and 37 GHz     

Agent-based evolutionary approach for interpretable rule-based knowledge extraction

An agent-based evolutionary approach is proposed to extract interpretable rule-based knowledge. In the multiagent system, each fuzzy set agent autonomously determines its own fuzzy sets information, such as the number and distribution of the fuzzy sets. It can further consider the interpretability of fuzzy systems with the aid of hierarchical chromosome formulation and interpretability-based regulation method. Based on the obtained fuzzy sets, the Pittsburgh-style approach is applied to extract fuzzy rules that take both the accuracy and interpretability of fuzzy systems into consideration. In addition, the fuzzy set agents can cooperate with each other to exchange their fuzzy sets information and generate offspring agents. The parent agents and their offspring compete with each other through the arbitrator agent based on the criteria associated with the accuracy and interpretability to allow them to remain competitive enough to move into the next population. The performance with emphasis upon both the accuracy and interpretability based on the agent-based evolutionary approach is studied through some benchmark problems reported in the literature. Simulation results show that the proposed approach can achieve a good tradeoff between the accuracy and interpretability of fuzzy systems.     

Decision-theoretic approach to visual inspection using neuralnetworks

The Bayesian real-time network (BARTIN) is applied to solving a visual-inspection problem requiring translation, rotation and scale (TRS) invariance. The system is capable of classifying n-fold symmetric engineering parts from near-axial views which may contain more than one part. It is evaluated and compared with other approaches using real visual-inspection data. A novel TRS-invariant preprocessor, the polygon transform, which is optimised for near-circular objects, provides information about the line and circle structure in two-dimensional images. An integral part of the polygon transform is a new Hough transform for circle radii used for both scale invariance and image characterisation. The BARTIN formalism is presented from the viewpoint of subjective Bayesian analysis, and this approach demonstrates how the personal probabilities and utilities of BARTIN can be used to optimise an externally provided reward function. A method is given for adjusting the global level of caution. To handle sparse training data, parameter parsimony in the observer was achieved using a structure comprising a stripped-out Parzen-windows classifier followed by a softmax perceptron trim. For real-time operation, the system is initialised by pretraining it using data extracted from design drawings